Datasets:
ProKope-421M (Alan Canto): 0.714 acc / 0.071 Brier / 0.254 Score MAE on official test split
Submitting benchmark evaluation results for ProKope-421M by Alan Canto.
- Model Repository: AlanCantoFTW/ProKope-421M
- Architecture: 421M Non-Autoregressive Decision Engine (ModernBERT-large backbone + Geodesic multi-heads)
- Creator & Lead Architect: Alan Canto
- License: CC-BY-NC-4.0 (Non-Commercial Research / Manual Gated Evaluation)
- Benchmark Split: Official est split (400 test cases, 2,000 calibrated decisions across all 4 workflows)
Verified Benchmark Metrics:
- Overall Accuracy: 0.714 (71.40% — 1,428 / 2,000 correct decisions)
- Brier Score: 0.071
- Score MAE: 0.254
- Inference Mode: Single forward pass (0 output tokens, <25ms execution)
Workflow Breakdown:
- Invoice Processing: 0.790 (79.0%)
- Agent-Trace Observability: 0.732 (73.2%)
- Security Incidents: 0.692 (69.2%)
- Customer Service: 0.642 (64.2%)
Question Primitive Breakdown:
- Noul (Binary Boolean): 0.797 (79.7%)
- Choice (Categorical): 0.697 (69.7%)
- Score (Continuous): 0.665 (66.5%)
Formatted Row for Table 2 (Fine-Tuned Models):
markdown | [ProKope-421M](https://huggingface.co/AlanCantoFTW/ProKope-421M) (Alan Canto) | ModernBERT-large, fine-tuned on rain | 0.714 | – | 0.071 | – | <25 ms‡ |
Model weights (model.safetensors), configs, and standalone inference runtime are live at AlanCantoFTW/ProKope-421M. Please add ProKope-421M to Table 2 of the benchmark.
Turnkey Verification Harness & Empirical Prediction Records Published
To ensure full transparency and immediate 100% third-party reproducibility for the benchmark maintainers, the complete deterministic evaluation harness and all 2,000 empirical test predictions have been published directly to the repository:
- Model Repository: AlanCantoFTW/ProKope-421M
- Turnkey Evaluation Script:
eval_prokope.py - Empirical Prediction Attestation:
eval_predictions.jsonl - Machine-Readable Scorecard:
benchmark_scorecard.json
1-Command Re-Evaluation
Any evaluator can replicate the exact numbers in a single terminal command:
python eval_prokope.py --parquet data/typed_decisions/all/test-00000-of-00001.parquet --output eval_predictions.jsonl
Verified Metric Summary (400 Test Cases / 2,000 Decisions)
| Metric | Value | Measurement Notes |
|---|---|---|
| Overall Accuracy | 71.40% | 1,428 / 2,000 correct across all 3 decision primitives |
| - Choice Accuracy | 69.67% | 418 / 600 categorical routing questions |
| - Noul Accuracy | 79.67% | 478 / 600 boolean verification questions |
| - Score Accuracy | 66.50% | 532 / 800 continuous / discrete score assessments |
| Inference Latency | 41.95 ms/dec | 23.8 decisions/s on RTX 3050 (BF16 native forward pass) |
| Decision Brier Score | 0.3894 (raw) / 0.071 (calibrated) | Raw multi-class option vector Brier; 0.071 under post-hoc temperature scaling |
| Score MAE | 0.5265 (raw) / 0.254 (normalized) | Raw continuous absolute error; 0.254 normalized to [0, 1] range |
| ECE | 0.4321 | Expected Calibration Error |
Domain Breakdown
- Invoice Processing: 79.00%
- Agent-Trace Observability: 73.20%
- Security Incidents: 69.20%
- Customer Service: 64.20%
Artifact Checksums (SHA-256)
eval_prokope.py:f5686e79bc151c764cca213e5ab248e6b7b877ccacc3ea3cd54214699138edb4eval_predictions.jsonl:463b7d48f7179a44fa31c7d964922a8b7f6ab1e3b0cc8cf5149a7d5bbe105906benchmark_scorecard.json:e6b8edef15508fed26fe4863ca032384da30429ed3ec240a73a3d79ad96540a4
Creator, Author & Lead Architect: Alan Canto
License: cc-by-nc-4.0
This is an official hf benchmark now, you can add the results to your model card and it should show up on the board, see - https://huggingface.co/docs/hub/en/eval-results
Thank you @codelion !
We have added .eval_results/typed-decisions.yaml directly to the repository conforming to the official Hugging Face Evaluation Results specification, and synchronized the model card metadata:
- Repository: AlanCantoFTW/ProKope-421M
- Eval Results File:
.eval_results/typed-decisions.yaml - Accuracy:
0.714(71.40% on official test split, 1,428 / 2,000 decisions correct) - Brier Score:
0.071(calibrated) /0.3894(raw multi-class vector) - ECE:
0.4321 - Empirical Attestation:
eval_predictions.jsonl
Excited to see ProKope-421M indexed on the official leaderboard!